metadata
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert_product_classifier_name
results: []
bert_product_classifier_name
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3406
- Accuracy: 0.9517
- F1: 0.9513
- Precision: 0.9514
- Recall: 0.9517
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.8574 | 1.0 | 960 | 0.3075 | 0.9079 | 0.9069 | 0.9077 | 0.9079 |
| 0.267 | 2.0 | 1920 | 0.2432 | 0.9292 | 0.9294 | 0.9307 | 0.9292 |
| 0.1596 | 3.0 | 2880 | 0.2228 | 0.9411 | 0.9408 | 0.9409 | 0.9411 |
| 0.1094 | 4.0 | 3840 | 0.2540 | 0.9452 | 0.9447 | 0.9447 | 0.9452 |
| 0.0755 | 5.0 | 4800 | 0.2652 | 0.9470 | 0.9471 | 0.9472 | 0.9470 |
| 0.0506 | 6.0 | 5760 | 0.2924 | 0.9492 | 0.9491 | 0.9491 | 0.9492 |
| 0.0364 | 7.0 | 6720 | 0.3251 | 0.9475 | 0.9470 | 0.9476 | 0.9475 |
| 0.022 | 8.0 | 7680 | 0.3271 | 0.9518 | 0.9515 | 0.9514 | 0.9518 |
| 0.0122 | 9.0 | 8640 | 0.3368 | 0.9522 | 0.9520 | 0.9519 | 0.9522 |
| 0.0103 | 10.0 | 9600 | 0.3406 | 0.9517 | 0.9513 | 0.9514 | 0.9517 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3